Enhanced Eco-Approach Control of Connected Electric Vehicles at Signalized Intersection With Queue Discharge Prediction

被引:43
|
作者
Dong, Haoxuan [1 ]
Zhuang, Weichao [1 ]
Chen, Boli [2 ]
Yin, Guodong [1 ]
Wang, Yan [1 ]
机构
[1] Southeast Univ, Sch Mech Engn, Nanjing 211189, Peoples R China
[2] UCL, Dept Elect & Elect Engn, London WC1E 6BT, England
基金
国家杰出青年科学基金;
关键词
Energy efficiency; Discharges (electric); Vehicle dynamics; Traction motors; Force; Wheels; Torque; Electric vehicles; connected vehicles; eco-driving; energy efficiency; velocity planning; dynamic programming; AUTOMATED VEHICLES; ENERGY MANAGEMENT; DRIVING STRATEGY; HYBRID; CONSUMPTION; EFFICIENCY; PROFILE; DESIGN; SCHEME;
D O I
10.1109/TVT.2021.3075480
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Long queues of vehicles are often found at signalized intersections, which increases the energy consumption of all the vehicles involved. This paper proposes an enhanced eco-approach control (EEAC) strategy with consideration of the queue ahead for connected electric vehicles (EVs) at a signalized intersection. The discharge movement of the vehicle queue is predicted by an improved queue discharge prediction method (IQDP), which takes both vehicle and driver dynamics into account. Based on the prediction of the queue, the EEAC strategy is designed with a hierarchical framework: the upper-stage uses dynamic programming to find the general trend of the energy-efficient speed profile, which is followed by the lower-stage model predictive controller to computes the explicit solution for a short horizon with guaranteed safe inter-vehicular distance. Finally, numerical simulations are conducted to demonstrate the energy efficiency improvement of the EEAC strategy. Besides, the effects of the queue prediction accuracy on the performance of the EEAC strategy are also investigated.
引用
收藏
页码:5457 / 5469
页数:13
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